1. Field
One or more embodiments of the present disclosure relate to a method and apparatus for generating hierarchical saliency images with selective refinement.
2. Description of the Related Art
Recently, there has been an increased interest in saliency extraction schemes in the computer vision and image processing field.
One saliency extraction scheme uses the random walk theory to convert the image into a graph in order to obtain the saliency of nodes of the image.
In this scheme, the image may be divided into blocks and each divided block may be defined as a node. An edge weight is set using a movement frequency relation between a plurality of nodes, and a transition matrix capable of converting the set edge weight, which is displayed as a matrix, into a Markov chain form, may be produced.
According to the random walk theory, the steady-state distribution produced in the transition matrix may become the frequency with which each node may be “visited” or viewed by a human viewer. A node is said to have a high visiting frequency if it is in an area that a human viewer looks at frequently. Hence, the saliency of each node may be detected using the steady-state distribution.